{"title":"改善带分布式能源资源和储能的降压控制直流微电网系统性能的优化配置","authors":"Dinto Mathew, Prajof Prabhakaran","doi":"10.1016/j.compeleceng.2024.109809","DOIUrl":null,"url":null,"abstract":"<div><div>The placement of sources and loads in DC microgrids (DCMGs) influences the system’s voltage regulation, span, and losses. In order to minimize losses and enhance voltage regulation, a unique algorithm for configuring a radial DCMG under droop control in an optimal way is presented in this paper. The suggested approach solves the optimal design problem by applying the power flow analysis technique. The genetic algorithm (GA), a heuristic method, is used to determine the ideal configuration because of the complexity of the optimization problem. An improved particle swarm optimization (IPSO)-based technique is also proposed for resolving the optimization issue to improve the convergence rate and computing efficiency. Appropriate modifications are proposed to yield an optimal configuration that results in the maximum achievable span for the radial, droop-controlled DCMG. To limit the bus voltage variations within the bounds, the objective functions of the optimization problem are appropriately formulated. In addition, the proposed algorithm is used to find the best position and power rating of a new distributed energy resource (DER) or load in the DCMG, in order to reduce system losses. A 5-bus, 500 W, radial, droop-controlled DCMG system’s comprehensive numerical and simulation results are presented to validate the effectiveness of the proposed approaches. The findings are significant and useful for DCMG consumers as well as system designers.</div></div>","PeriodicalId":50630,"journal":{"name":"Computers & Electrical Engineering","volume":"120 ","pages":"Article 109809"},"PeriodicalIF":4.0000,"publicationDate":"2024-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimal configuration for improved system performance of droop-controlled DC microgrid with distributed energy resources and storage\",\"authors\":\"Dinto Mathew, Prajof Prabhakaran\",\"doi\":\"10.1016/j.compeleceng.2024.109809\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The placement of sources and loads in DC microgrids (DCMGs) influences the system’s voltage regulation, span, and losses. In order to minimize losses and enhance voltage regulation, a unique algorithm for configuring a radial DCMG under droop control in an optimal way is presented in this paper. The suggested approach solves the optimal design problem by applying the power flow analysis technique. The genetic algorithm (GA), a heuristic method, is used to determine the ideal configuration because of the complexity of the optimization problem. An improved particle swarm optimization (IPSO)-based technique is also proposed for resolving the optimization issue to improve the convergence rate and computing efficiency. Appropriate modifications are proposed to yield an optimal configuration that results in the maximum achievable span for the radial, droop-controlled DCMG. To limit the bus voltage variations within the bounds, the objective functions of the optimization problem are appropriately formulated. In addition, the proposed algorithm is used to find the best position and power rating of a new distributed energy resource (DER) or load in the DCMG, in order to reduce system losses. A 5-bus, 500 W, radial, droop-controlled DCMG system’s comprehensive numerical and simulation results are presented to validate the effectiveness of the proposed approaches. The findings are significant and useful for DCMG consumers as well as system designers.</div></div>\",\"PeriodicalId\":50630,\"journal\":{\"name\":\"Computers & Electrical Engineering\",\"volume\":\"120 \",\"pages\":\"Article 109809\"},\"PeriodicalIF\":4.0000,\"publicationDate\":\"2024-11-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computers & Electrical Engineering\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0045790624007365\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers & Electrical Engineering","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0045790624007365","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE","Score":null,"Total":0}
Optimal configuration for improved system performance of droop-controlled DC microgrid with distributed energy resources and storage
The placement of sources and loads in DC microgrids (DCMGs) influences the system’s voltage regulation, span, and losses. In order to minimize losses and enhance voltage regulation, a unique algorithm for configuring a radial DCMG under droop control in an optimal way is presented in this paper. The suggested approach solves the optimal design problem by applying the power flow analysis technique. The genetic algorithm (GA), a heuristic method, is used to determine the ideal configuration because of the complexity of the optimization problem. An improved particle swarm optimization (IPSO)-based technique is also proposed for resolving the optimization issue to improve the convergence rate and computing efficiency. Appropriate modifications are proposed to yield an optimal configuration that results in the maximum achievable span for the radial, droop-controlled DCMG. To limit the bus voltage variations within the bounds, the objective functions of the optimization problem are appropriately formulated. In addition, the proposed algorithm is used to find the best position and power rating of a new distributed energy resource (DER) or load in the DCMG, in order to reduce system losses. A 5-bus, 500 W, radial, droop-controlled DCMG system’s comprehensive numerical and simulation results are presented to validate the effectiveness of the proposed approaches. The findings are significant and useful for DCMG consumers as well as system designers.
期刊介绍:
The impact of computers has nowhere been more revolutionary than in electrical engineering. The design, analysis, and operation of electrical and electronic systems are now dominated by computers, a transformation that has been motivated by the natural ease of interface between computers and electrical systems, and the promise of spectacular improvements in speed and efficiency.
Published since 1973, Computers & Electrical Engineering provides rapid publication of topical research into the integration of computer technology and computational techniques with electrical and electronic systems. The journal publishes papers featuring novel implementations of computers and computational techniques in areas like signal and image processing, high-performance computing, parallel processing, and communications. Special attention will be paid to papers describing innovative architectures, algorithms, and software tools.